Evo 2 is a genomic foundation model trained on the DNA of more than 100,000 species spanning all domains of life, on roughly 9 trillion nucleotides.

At 40B parameters it is described as the largest AI model for biology to date, with context up to 1 million nucleotides and a new StripedHyena 2 architecture. It can flag disease-causing mutations and generate coding-rich sequences up to a million bases long; Arc says 16 of 285 designed phage genomes were viable in lab testing. Training data, training and inference code, and model weights were all released, with the model integrated into NVIDIA BioNeMo alongside an interpretability visualizer.

Microsoft announced Majorana 1, a quantum processor it says is the first powered by a topological core, with eight topological qubits on a chip designed to scale toward a million.

The claim rests on a peer-reviewed Nature paper describing a hardware-protected topological qubit built from an indium-arsenide and aluminum stack Microsoft calls a topoconductor, plus a measurement technique precise enough to read the parity state of a superconducting nanowire. DARPA moved Microsoft into the final phase of its program to build a fault-tolerant prototype in years rather than decades. Microsoft says the chip will not be offered through Azure.

xAI unveiled Grok 3 and began rolling it out to X Premium+ subscribers, plus a new $30 per month SuperGrok tier.

xAI says the family was trained on its Colossus supercluster with roughly 10x the compute of previous state-of-the-art models — reporting put the Memphis cluster at around 200,000 GPUs — and that reasoning was refined through reinforcement learning at large scale, letting Grok 3 think for seconds to minutes. xAI claims an Elo of 1402 on Chatbot Arena and leads over GPT-4o on AIME and GPQA; Grok 3 mini targets cost-efficient reasoning, and DeepSearch shipped as a research agent. Grok 3 is closed, but Musk said Grok 2 will be open-sourced once Grok 3 is mature and stable, which he estimated at a few months. Two days later xAI made Grok 3 free to all users until our servers melt.

Perplexity released R1-1776, a post-trained version of DeepSeek-R1 whose weights can be downloaded and self-hosted.

R1-1776 keeps the base architecture: a 671-billion-parameter mixture-of-experts model with 37 billion active parameters and a 128K context window, released under the MIT license and also served through Perplexity's hosted API. Perplexity said it employed human experts to identify roughly 300 censored topics, built a dataset of 40,000 multilingual prompts, and fine-tuned using an adapted NVIDIA NeMo pipeline, reporting that math and reasoning performance held at parity with base R1.

OpenAI published SWE-Lancer, a benchmark of 1,488 freelance software engineering tasks drawn from Upwork and built around Expensify's codebase, representing $1,000,000 in real payouts actually made to the freelancers who did the work.

Tasks split into independent-contribution tickets — from $50 bug fixes to $32,000 feature implementations — and managerial decisions where the model picks between competing implementation proposals. Grading uses end-to-end tests written by professional engineers rather than unit tests. Claude 3.5 Sonnet did best, completing 26.2% of the hands-on coding tasks and 44.9% of the management decisions; OpenAI's own note was that frontier models are still unable to solve the majority of tasks.